Every Product Will Be a Data Product

Published in

Kyligence

6 min readDec 2, 2021

Why Build a Data Product?

As software has eaten the world, every software company is becoming a SaaS Company, and every SaaS company has a massive volume of data. As organizations transition to data-driven decision-making, they require the adopted SaaS products to provide in-product analysis abilities or data API to support their thriving needs on data.

The benefits of such data products for the SaaS company are:

The data economy: Maintaining data assets is a cost, but turning them into products generates business value (and revenue).
Agile and flexible business: Products can scale with business expansion but not data. Data itself cannot be scaled without a companion architecture.
Democratize your data: Everyone should be able to interact with a product, but not necessarily a dataset!

What Is a Data Product?

You might have the same question in mind as me: What exactly is a data product?

As defined by DJ Patil, the US chief data scientist, a data product is “a product that facilitates an end goal through the use of data”.

From my perspective, data products can sometimes be synonymous with data applications. For the general consumer, as we all experience in our daily life, it can be either a product that provides a digital banking statement or a COVID-19 cases tracker like this one.

The end-users can consume the data within the proper context and quickly make sense of the data.

Different Types of Data Products

Conceptually, depending on the user persona and the use cases, there are 4 different types of data products:

There are more examples to demonstrate different types of data products.

Use case 1: The data product will be the Public API that the company exposes to internal or external data engineers/developers who can consume or develop to another layer of a data product. In this case, the data product producer will be an application developer who will build the API for the consumer.
Use case 2: The data product is mainly used for internal decision-making support purchases. The internal data team is the data product producer in this use case. Data engineers and analysts prepare the data pipeline and data model for business users to perform self-service analysis. Power analysts will design the canned dashboard for business owners and business stakeholders to view on a given frequency set.
Use case 3: These data products can be prepared by the citizen developers (line of business users) for automating or streamlining internal repetitive business processes. Citizen developers use low-code/no-code applications such as Microsoft Power Apps to build their internal business applications.
Use case 4: These are the data products that are part of the external applications/SaaS services that the company provides to their end customers. In this use case, the application developer will be the data product producer who calls the data API as part of the application backend and builds the Web/Mobile front-end UI for the end-users to consume.

Some Real Customer Examples

Next, I will share some of the typical customer stories of different data product use cases.

AppZen Builds their Mastermind Analytics Product in Weeks

AppZen overhauls how finance teams work, automating spend approvals and providing insights that help finance auditors reduce spending, comply with the policy, and streamline processes.

What AppZen achieved:

AppZen built a data product during the CoVID-19 pandemic.
Hundreds of customers onboarded in 12 months.
There was a 90% increase in auditing process efficiency.
They created a scalable and cost-effective architecture.
AWS S3 + Kyligence + Apache Superset

How Kyligence Helps AppZen Build Its Data Product

Kyligence provides:

A high-performant, high-concurrent data service natively on AWS.
A rich set of APIs (ODBC, JDBC, Rest API, Python Client) to have a wide range of options for integrating and building the data product front-end.
A flexible data service supporting queries of summarized high-risk reports and expense line details.

Combining Kyligence and Apache Superset, AppZen can provide rich self-service audit analytic dashboards and reports to the expense auditor. As a result, the auditor can now have visibility of expenses at all levels with summarized and detailed data consistency.

Strikingly Provides Its 100,000 Website Builders Built-in Analytics Service with Ease

Strikingly is one of the best free website builders for anyone to easily create a gorgeous, mobile-friendly website. Strikingly provides Built-in Analytics, a Google Analytics-like website traffic analyst for its website builders.

Strikingly Built-in analytics gives end-user information about unique visitors, top country, top pages, countries of visitors, devices, and traffic sources.

How Kyligence Helps Strikingly Build Their Built-in Analytics

Kyligence helps Strikingly with:

Providing a data service that enables website builders to perform traffic analytics
Reducing TCO with better performance
Managing services offered by Kyligence to take over data service operations

Summary

In this blog, I explained my understanding of data products, four common use case, and how Kyligence helps empower SaaS companies provide their in-apps data products to end-users.

If you are interested in the data product solutions Kyligence provides, here is what you can try as a next step:

You can try out playground, which can give you a taste of how Kyligence can inspect your SQL queries and recommend data models with a few clicks.
You can also test drive the full version of Kyligence on the hosted cloud environment.